| #!/usr/bin/python |
| |
| import random |
| |
| class Distribution: |
| """Represents a normal distribution""" |
| |
| def __init__(self, meanx, meany, stddev): |
| self.meanx = meanx |
| self.meany = meany |
| self.stddev = stddev |
| |
| def sample(self): |
| x = random.gauss(self.meanx, self.stddev) |
| y = random.gauss(self.meany, self.stddev) |
| return x, y |
| |
| |
| if __name__ == '__main__': |
| import sys |
| if len(sys.argv) == 1: |
| print "Usage: python datagen.py <#points> <avg x,avg y,standard dev>+" |
| sys.exit(1) |
| |
| numpoints = int(sys.argv[1]) |
| |
| distributions = [] |
| for arg in sys.argv[2:]: |
| parsedargs = map(float, arg.split(',')) |
| distributions.append(Distribution(*parsedargs)) |
| |
| linecount = 0 |
| while linecount < numpoints: |
| distribution = distributions[linecount % len(distributions)] |
| x, y = distribution.sample() |
| print '{:.5f},{:.5f}'.format(x, y) |
| linecount += 1 |
| |
